Presentations

SU-E-708-5 (Sunday, July 30, 2017) 1:00 PM - 1:55 PM Room: 708

Purpose: Radiomic analysis has witnessed significant activity especially in oncologic MRI, CT and PET, but remains to be thoroughly assessed in SPECT and/or cardiac imaging. We aimed to assess the reproducibility and reliability of textural (radiomic) features in ⁹⁹ᵐTc-Sestamibi Myocardial-Perfusion SPECT (MPS) images, and to derive robust features for correlation with clinical outcomes.

Methods: 94 patients were selected with normal (non-ischemic) stress MPS scans (injected with 8-30mCi ⁹⁹ᵐTc-sestamibi). Images were iteratively reconstructed (attenuation-corrected, isotropic-cubic-voxels), and verified by nuclear medicine physician to be free from two common MPS artifacts: image overcorrection, and liver spillover. Semi-automatic segmentation and polar map generation was performed (MIM Software™) under radiologist supervision, to generate: A) total-myocardium, B) three-region vascular (LAD-RCA-LCX), and C) 17 polar segments. Images were uniformly quantized with various gray-levels (4,8,16,32,64,128,256,512). 85 radiomic features were generated. For A-B-C segmentation scales, Spearman’s rank-correlation was calculated between 512 gray-levels and each of 7 other gray-levels to select relatively consistent quantization levels. The intra-class correlation (ICC) between remaining gray-levels across all patients was used to adopt robust features across each segmentation model.

Results: Maximum count in images varied substantially (3,428-42,761). Morphological and moment-invariant features should be left out due to standardized segmentation. Consistent Spearman-correlation≥0.6 was observed for gray-levels≥128 for B-scale and ≥64 for C-scale. At A-scale (myocardium), dissimilarly showed a relatively consistent correlation across all gray-levels. ICC, averaged over all segments within A,B,C, was ≥0.8 for 19,19,16 features and ≥0.9 for 13,11,7 features, respectively. Shared features with ICC≥0.9 include: skewness, kurtosis(hist), entropy,variance,correlation,IDMN(GLCM), RLN(GLRLM). ICC≥0.8 further includes entropy(hist), differenceentropy,IDN(GLCM), LGRE,SRLGE(GLRLM) and ZSN,LGZE(GLSZM) to this set.

Conclusion: Quantization by 128 or 256 gray-levels is suggested for capturing heterogeneity information. A set of 14 reproducible and robust features were identified, some of which have demonstrated reproducibility in other modalities, and are recommended for further investigation of predictive or prognostic values.